Electroencephalographic neurofeedback: level of evidence in mental and brain disorders and suggestions for good clinical practice
Abstract
The technique of electroencephalographic neurofeedback (EEG NF) emerged in the 1970s and is a technique that measures a subject's EEG signal, processes it in real time, extracts a parameter of interest and presents this information in visual or auditory form. The goal is to effectuate a behavioural modification by modulating brain activity. The EEG NF opens new therapeutic possibilities in the fields of psychiatry and neurology. However, the development of EEG NF in clinical practice requires (i) a good level of evidence of therapeutic efficacy of this technique, (ii) a good practice guide for this technique. Firstly, this article investigates selected trials with the following criteria: study design with controlled, randomized, and open or blind protocol, primary endpoint related to the mental and brain disorders treated and assessed with standardized measurement tools, identifiable EEG neurophysiological targets, underpinned by pathophysiological relevance. Trials were found for: epilepsies, migraine, stroke, chronic insomnia, attentional-deficit/hyperactivity disorder (ADHD), autism spectrum disorder, major depressive disorder, anxiety disorders, addictive disorders, psychotic disorders. Secondly, this article investigates the principles of neurofeedback therapy in line with learning theory. Different underlying therapeutic models are presented didactically between two continua: a continuum between implicit and explicit learning and a continuum between the biomedical model (centred on "the disease") and integrative biopsychosocial model of health (centred on "the illness"). The main relevant learning model is to link neurofeedback therapy with the field of cognitive remediation techniques. The methodological specificity of neurofeedback is to be guided by biologically relevant neurophysiological parameters. Guidelines for good clinical practice of EEG NF concerning technical issues of electrophysiology and of learning are suggested. These require validation by institutional structures for the clinical practice of EEG NF.
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NFB is most commonly used for attention and hyperactivity disorders, depression disorders, stroke, epilepsy, migraine and chronic insomnia.
“Attention and hyperactivity disorders, depression disorders, stroke, epilepsy, migraine and chronic insomnia are some of the conditions for which NFB is most commonly used.4”
No explicit strategies or instructions were given because implicit strategies have been shown to produce better outcomes.
“Notably, no explicit strategies or instructions were given as, with few exceptions [204], implicit strategies have been shown to produce better outcomes [205–210].”
Manual, rather than automated, thresholding was chosen because it has been reported to lead to better EEG-learning.
“Manual, rather than automated, thresholding was chosen as it has been reported to lead to better EEG-learning [125, 173, 206, 208].”
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- Authors
- Micoulaud-Franchi, J.-A., McGonigal, A., Lopez, R., Daudet, C., Kotwas, I., & Bartolomei, F.
- Affiliations
- Inserm (FR)
- Hôpital Gui de Chauliac (FR)
- Université de Bordeaux (FR)
- Aix-Marseille Université (FR)
- Venue
- Neurophysiologie Clinique/Clinical Neurophysiology
- Publisher
- Elsevier BV
- Published
- 2015-12
- Volume
- 45
- Issue
- 6
- Pages
- 423-433
- ISSN
- 0987-7053 (ISSN-L)
- OpenAlex
- W2194336409
- Cited by
- 111
- References
- 113
- Citations by year
- 2026: 6 · 2025: 8 · 2024: 10 · 2023: 6 · 2022: 13 · 2021: 16 · 2020: 14 · 2019: 13 · 2018: 9 · 2017: 8 · 2016: 8
- FWCI
- 0.83
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Neurophysiologie Clinique (publishedVersion)
- PubMed (publishedVersion)
- HAL (submittedVersion)
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › EEG and Brain-Computer Interfaces
- Life Sciences › Neuroscience › Neurology › Transcranial Magnetic Stimulation Studies
- Social Sciences › Psychology › Clinical Psychology › Psychotherapy Techniques and Applications
- Keywords
- neurofeedback, level of evidence, mental illness, brain disorders, epilepsy, migraine, stroke, chronic insomnia, attention deficit hyperactivity disorder, autism spectrum disorder, major depressive disorder, anxiety disorders, addiction, psychosis, explicit and implicit learning, biopsychosocial model, cognitive remediation, learning theory, treatment efficacy
- MeSH terms
- Mental Disorders, Brain Diseases, Electroencephalography, Humans, Evidence-Based Medicine, Neurofeedback
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